Architect

Hiring: Architect AI, Data Science & Data Engineering

Location: Bangalore/Hyderabad/Chennai (Onsite)

Experience: 815 years

Employment Type: Full-time

We are hiring a strong AI, Data Science & Data Engineering Architect. This is a senior, hands-on leadership role for someone who can set technical direction, design enterprise-scale AI and data platforms, guide architecture decisions, and mentor multidisciplinary engineering teams.

The ideal candidate should have strong depth across AI/ML, Generative AI, Data Science, Data Engineering, Cloud Architecture, MLOps/LLMOps, and enterprise consulting/client-facing delivery.

Key Responsibilities:

• Own the technical vision and architecture for complex AI, data science, and data engineering initiatives.
• Lead design reviews, architecture discussions, and high-impact technical decisions.
• Build and guide modern cloud-native and AI-native reference architectures.
• Lead GenAI, agentic AI, ML, NLP, computer vision, graph ML, reinforcement learning, and LLM-related solution design.
• Architect AI-ready data platforms with scalable pipelines, governance, observability, metadata management, and lineage.
• Define responsible AI, model evaluation, and reliability practices.
• Drive R&D, prototype new AI ideas, and convert research into practical enterprise solutions.
• Engage with enterprise clients as a senior technical voice during discovery, solution framing, and architecture discussions.
• Hire, mentor, and grow engineers, ML practitioners, data engineers, and architects.

Required Skills & Experience

• 815 years of overall experience in AI, Data Science, Data Engineering, or related technology leadership roles.
• Strong hands-on experience across machine learning, data science, GenAI, LLMs, NLP, computer vision, graph ML, and agentic AI.
• Deep experience in modern data engineering, cloud-native architecture, DataOps, governance, MLOps, and LLMOps.
• Architecture-level fluency in at least one major cloud platform: AWS, GCP, or Azure.
• Experience with enterprise-scale data pipelines, AI platforms, and production-grade ML/AI systems.
• Comfort with Temporal or similar durable workflow orchestration platforms for long-running data, ML, and agentic workflows.
• Strong consulting, professional services, or enterprise product engineering background.
• Ability to communicate clearly with both engineering teams and senior business stakeholders.
• Experience leading teams through ambiguous, research-heavy problems to working production solutions.

Nice to Have

• Experience building or scaling an AI/ML or data engineering practice.
• Hands-on exposure to RAG, agentic workflows, AI evaluation frameworks, and LLMOps.
• Domain experience in retail, financial services, manufacturing, healthcare, or technology.
• Public thought leadership through talks, publications, open-source work, or reference architectures.
• Experience managing distributed or multi-country engineering teams.